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We have laws for just about everything from personal laws to commercial, contractual, e-discovery, and list goes on and on…

What’s important is to understand the ‘implementation’ of such laws! In my experience, as an attorney, I have come across hundreds of laws from all the way from legislation to the point when they are repealed! Laws have been around for a long time, yet we regularly find instances/cases where person suffered illegal detention, false imprisonment, and so forth.

The litigation hold in the process of e-discovery can be summed up in the following definition:

A litigation hold is a written directive advising custodians of certain documents and electronically-stored information (ESI) to preserve potentially relevant evidence in anticipation of future litigation

Well, easier said than done! In the NuVasive, Inc. v. Madsen Med., Inc., No. 13cv2077, 2015 WL 4479147 (S.D. Cal. July 22, 2015) case, simply implementing a legal hold was not enough to satisfy a party’s duty to preserve. Instead, the party must take affirmative steps to implement the hold, follow up with custodians to ensure data preservation, and also ensure that the hold covers all forms of data, including text messages and other emerging data formats.

Well, that seems like and, in fact, is a daunting task. In today’s computing scenario, where majority of the time the workforce is mobile, and not to mention the influx of mobile devices each of us have an use – then we try to remember “Where in the world did I save/store that document” – you get the point.

Within the realm of e-discovery, litigation can be reduced by providing an indispensable, seamless, and a fully collaborative platform/solution so that documents, text messages, and voice can be saved in repositories. Proactive approach towards data compliance will reduce costs in the long run for corporations!

While the future of e-discovery may rest on the foundation of information governance, a wise and proactive approach with special emphasis on building efficient processes, and more importantly automating those processes within the organization must be adopted to reduce legal complexities.

Here’s a sample tutorial of what SharePoint/Office 365 Compliance Center can help you achieve!

Outsourcing is now a common phenomena among businesses. Essentially, you contract out a business process to a third party, both foreign and domestic contracting – at times relocating a business function to another country. Traditionally speaking, companies having financial difficulties didn’t have much choice but to restructure, lay-off employees or incur additional debt to cover short term obligations. Outsourcing of redundant business processes came as a sigh of relief for many, especially large corporations with humongous overheads. The incentive to outsource may be greater for U.S. companies due to unusually high corporate taxes and mandated benefits such as Social Security, Medicare, and Occupational Safety and Health Administration (OSHA) regulations.

Now that you have successfully outsourced and established a cordial relationship with your vendor, industry trends may change that require you to focus more on certain business segments. Insourcing has been identified as a means to ensure control, compliance and to gain competitive differentiation through vertical integration or the development of shared services (commonly called a ‘center of excellence’).

But wait a minute! It seems like you require both in order to attain a lean and optimal cost effectiveness business model.

E-Discovery Industry:

For the last decade or so, e-Discovery industry has experienced tremendous growth in terms of outsourcing mainly due to escalating costs. The result – growing number of captive centers all over the world, especially with abundant labor resources such as India, Pakistan, and Philippines. The biggest cost driver in e-Discovery is document review – over 60 percent of total costs, one of the main reasons of influx of captive offshore centers or outsourcing. Recently, however, law school graduates in the US, for instance, have been accepting employment at all time low wages – making it increasingly competitive for e-Discovery vendors.

What’s an optimal solution?

According to Balanced Score Card Institute, “The balanced scorecard is a strategic planning and management system that is used extensively in business and industry, government, and nonprofit organizations worldwide to align business activities to the vision and strategy of the organization, improve internal and external communications, and monitor organization performance against strategic goals” Using this tool helps an organization to identify, understand, and evaluate core business processes, resulting in best practices of utilizing outsourcing and insourcing strategies.

Discovery has changed, and electronically stored information (ESI) was the facilitator. Though ediscovery matters are no longer the novel issues that they once were,” technology is constantly changing. According to Baseline, it was estimated that 90 percent of worlds data has been created in the last two years. in 2009 there were 988 Exabyte of data in existence, an amount that would stretch from the Sun to Pluto and back in paper form. The problem for corporations is the storage of huge amounts of data – let alone worry about the ‘compliance monster’.

Perhaps, cloud computing is here to ease things out, yet companies are retaining more information than ever, and lawsuits sometimes require attorneys review millions and millions of documents. While Judiciary struggles to devise effective mechanism regarding proportionality rules, big data is growing even bigger – not to mention growing litigation industry. It seems manual review of documents is not an option anymore, as technology is rushing towards meeting the growing needs of document review.

The most important element overlooked is the fact that human eyeballs are still required to review such documents leading to defensibility of the case; after all, isn’t that the real objective?

Definitions of “predictive coding” vary, but a common form of predictive coding includes the following steps. First, the data is uploaded onto a vendor’s servers. Next, representative samples of the electronic documents are identified. These “seed sets” can be created by counsel familiar with the issues, by the predictive coding software, or both. Counsel then review the seed sets and code each document for responsiveness or other attributes, such as privilege or confidentiality. The predictive coding system analyzes this input and creates a new “training set” reflecting the system’s determinations of responsiveness. Counsel then “train” the computer by evaluating where their decisions differ from the computers and then making appropriate adjustments regarding how the computer will analyze future documents.

This process is repeated until the system’s output is deemed reliable. Reliability is determined by statistical methods that measure recall—the percentage of responsive documents in the entire data set that the computer has located—and precision—the percentage of documents within the computer’s output set that are actually responsive. (That is, “recall” tests the extent to which the predictive coding system misses responsive documents, while “precision” tests the extent to which the system is mixing irrelevant documents in with the production set.) The resulting output can be either produced as is or further refined by subsequent human review. Subsequently, attorneys review a much smaller set of documents. Predictive coding therefore effectively “alleviates the need to review whole masses of records in order to find the relevant few.” Most importantly, predictive coding is estimated to reduce ediscovery costs as much as 40% to 60% while maintaining search quality.

A statistic quoted in an IDC and EMC report says that the digital universe is doubling every two years, and will reach 40,000 Exabyte (40 trillion gigabytes) by 2020. The question is: Can predictive coding cope up with big data?

The biggest cost driver in e-discovery is the document review part, where millions and millions of documents must be reviewed for potential relevancy and/or responsiveness. KPMG estimates that first level document review encompasses anywhere between 58% and 90% of total litigation costs. While predictive coding technologies have been somewhat successful in culling down most of the documents by utilizing an optimal combination of ‘recall’ and ‘precision’ values, human eyes are still required. Attorneys, senior paralegals power up review centers specifically designed for such projects only to find repetitive work day in day out – resulting in high turnover.

Typically, teams are rounded up and dismantled on an as-needed basis using attorneys, paralegals and law school graduates. This, in turn, has created a ‘day laborer’ mentality, as most projects are short term in nature, anywhere from a few days to months. Therefore, it is not uncommon for document review teams to start with 30 to 50 individuals, and during the course of the project to lose over half of the original members. With costs and inconsistencies in mind, high document reviewer turnover has not only affected the consistency of first level document review projects, but has led to an inefficient model of ‘training and re-training’, consequently resulting in escalation of costs.

Presently, though, due to influx of attorney workforce, pay rates have been seen to take a downward turn – a simple supply and demand situation.

The overall costs, however, remain high due to advent of ‘Big Data’. The question remains: How do you further reduce costs? There is good news!

Let me illustrate savings for a law firm or corporation in a simple hypothetical scenario:

Savings for the law firm of corporation by 50%, that is, save $600K – flat!

One can only imagine the cost savings in much larger engagements. These savings provide additional value and act as supplement to the predictive coding technology – together they form a true win-win solution for clients.